PDF hosted at the Radboud Repository of the Radboud University Nijmegen

The following full text is a publisher's version.

For additional information about this publication click this link. https://hdl.handle.net/2066/224857

Please be advised that this information was generated on 2021-10-07 and may be subject to change. Gut Microbes

ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/kgmi20

Growth rate alterations of human colorectal cancer cells by 157 gut bacteria

Rahwa Taddese , Daniel R. Garza , Lilian N. Ruiter , Marien I. de Jonge , Clara Belzer , Steven Aalvink , Iris D. Nagtegaal , Bas E. Dutilh & Annemarie Boleij

To cite this article: Rahwa Taddese , Daniel R. Garza , Lilian N. Ruiter , Marien I. de Jonge , Clara Belzer , Steven Aalvink , Iris D. Nagtegaal , Bas E. Dutilh & Annemarie Boleij (2020) Growth rate alterations of human colorectal cancer cells by 157 gut bacteria, Gut Microbes, 12:1, 1-20, DOI: 10.1080/19490976.2020.1799733 To link to this article: https://doi.org/10.1080/19490976.2020.1799733

© 2020 The Author(s). Published with license by Taylor & Francis Group, LLC.

View supplementary material

Published online: 11 Sep 2020.

Submit your article to this journal

View related articles

View Crossmark data

Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=kgmi20 GUT MICROBES 2020, VOL. 12, NO. 1, e1799733 (20 pages) https://doi.org/10.1080/19490976.2020.1799733

RESEARCH PAPER Growth rate alterations of human colorectal cancer cells by 157 gut bacteria Rahwa Taddese a*, Daniel R. Garza b*, Lilian N. Ruitera, Marien I. de Jonge c, Clara Belzer d, Steven Aalvink d, Iris D. Nagtegaal a, Bas E. Dutilhb,e, and Annemarie Boleij a aDepartment of Pathology, Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Center, Nijmegen, The Netherlands; bCentre for Molecular and Biomolecular Informatics, Radboud University Medical Center, Nijmegen, The Netherlands; cSection Pediatric Infectious Diseases, Laboratory of Medical Immunology, Radboud Center for Infectious Diseases (RCI), Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Center, Nijmegen, The Netherlands; dLaboratory of Microbiology, Wageningen University and Research, Wageningen, The Netherlands; eTheoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands

ABSTRACT ARTICLE HISTORY Several bacteria in the human gut microbiome have been associated with colorectal cancer (CRC) Received 27 January 2020 by high-throughput screens. In some cases, molecular mechanisms have been elucidated that drive Revised 26 June 2020 tumorigenesis, including bacterial membrane proteins or secreted molecules that interact with the Accepted 8 July 2020 human cancer cells. For most gut bacteria, however, it remains unknown if they enhance or inhibit KEYWORDS cancer cell growth. Here, we screened bacteria-free supernatants (secretomes) and inactivated cells Colorectal cancer; cell of over 150 cultured bacterial strains for their effects on cell growth. We observed family-level and proliferation; MTT assay; strain-level effects that often differed between bacterial cells and secretomes, suggesting that human microbiome; different molecular mechanisms are at play. Secretomes of Bacteroidaceae, Enterobacteriaceae, secretomes and Erysipelotrichaceae bacteria enhanced cell growth, while most Fusobacteriaceae cells and secretomes inhibited growth, contrasting prior findings. In some bacteria, the presence of specific functional genes was associated with cell growth rates, including the virulence genes TcdA, TcdB in Clostridiales and FadA in Fusobacteriaceae, which both inhibited growth. Bacteroidaceae cells that enhanced growth were enriched for genes of the cobalamin synthesis pathway, while Fusobacteriaceae cells that inhibit growth were enriched for genes of the ethanolamine utilization pathway. Together, our results reveal how different gut bacteria have wide-ranging effects on cell growth, contribute a better understanding of the effects of the gut microbiome on host cells, and provide a valuable resource for identifying candidate target genes for potential microbiome-based diagnostics and treatment strategies.

Introduction a process that is described by the bacterial driver- passenger model.6,7 Bacterial drivers may facilitate Over the past few decades, thousands of microbial the acquisition of hallmarks of cancer8 in mucosal species have been identified in the human gut cells by generating DNA-damage, reducing the microbiome. Each person harbors an estimated epithelial barrier function, and stimulating pro- 13 3.8 × 10 bacteria in their guts with a relatively carcinogenic immune responses. As the tumor 1–3 stable species composition. Changes in the com­ microenvironment changes in the transition from position of the gut microbiome have been linked adenoma to carcinoma, bacterial passengers com­ with various diseases including colorectal cancer pete with the drivers, further shifting the micro­ (CRC), the third leading cancer worldwide with biome toward a CRC signature.9,10 The newly an incidence that is estimated to rise in the coming acquired bacteria may in turn affect tumor devel­ 4,5 decennium. Besides important environmental opment, by potential inhibiting, enhancing, or neu­ and genetic factors, the initiation and development tral effects on tumor cell growth.6 These CRC- of CRC are affected by the human gut microbiome. specific changes offer the opportunity to use the During tumorigenesis, the bacterial composition bacterial community for diagnostic, prognostic, on the affected intestinal mucosa changes in preventive, and treatment measures.11–20

CONTACT Bas E.Dutilh [email protected] Centre for Molecular and Biomolecular Informatics, Radboud University Medical Center, Nijmegen, The Netherlands; Annemarie Boleij [email protected] Department of Pathology, Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Center, Nijmegen, The Netherlands *Equal contribution. Supplemental data for this article can be accessed here. © 2020 The Author(s). Published with license by Taylor & Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. e1799733-2 R. TADDESE ET AL.

In feces of CRC patients, the genera Fusobacterium, The aim of this study was to examine the effects Peptostreptococcus, Ruminococcus, and Escherichia/ of bacterial cells and their secretomes on the growth Shigella are enriched, while Bacteroides and rates of epithelial cells. We tested the effect of 157 Lachnospiraceae (Roseburia, Lachnospira, different gut bacteria on the growth rates of five Anaerostipes) have a lower relative CRC cell lines and one immortalized kidney cell abundance.5,9,11,21–25 Even though phyla such as line. Our results revealed that different bacterial Bacteroidetes are depleted, single species like entero­ families specifically inhibit or enhance cell growth, toxigenic Bacteroides fragilis may be enriched in some although contrasting effects could be observed CRC patients.25–27 Comparing tumor tissue with between some closely related strains. Both known adjacent normal tissue on the intestinal mucosa of virulence genes and novel microbial pathways were CRC patients revealed that Fusobacterium, associated with the different growth rate changes. Prevotella, Streptococcus, and Peptostreptococcus were These results provide the first large-scale in vitro enriched in tumors while Blautia, Escherichia, analysis of the effects of different microbial strains Pseudomonas, and Faecalibacterium were enriched on epithelial cell growth. in the normal mucosa.5,7,9,11,22-24,28 Many different bacteria have been associated with CRC tumors,10 but we are only beginning to under­ Materials and methods stand the different mechanisms that are involved. The Bacterial strains effect of bacteria on cell growth may be driven by direct bacterial-to-epithelial cell-cell contact or by We selected 116 different gut bacteria, including secreted products present in the secretome.29,30 species that are depleted or enriched in CRC Membrane-bound bacterial proteins that require cell- patients whose genome sequences were available cell contact can activate epithelial cell signaling. For in the PATRIC database.42 Additionally, we example, the passenger bacterium Fusobacterium selected specific bacteria without sequenced gen­ nucleatum encodes the membrane protein omes (n = 39) that were strongly linked to CRC Fusobacterium adhesin A (FadA) that binds to or were isolated from CRC tissue, including E-cadherin, activating β-catenin signaling and result­ Streptococcus bovis,43,44 Clostridium septicum,44–46 ing in increased tumor growth.31–33 Specific E. coli Clostridioides difficile,47,48 Bacteroides sp.27 and the species with the eae gene express the adhesin protein two potentially beneficial bacteria Lactobacillus intimin on their membrane surface which binds to casei Shirota49-51and Akkermansia muciniphila and causes lesions to gut epithelial cells, allowing ATCC BAA-835TM.52-55 Together, we analyzed bacteria to breach the colonic barrier. Once the bac­ 157 bacterial strains isolated from the human gut teria are bound to the epithelial cells, this allows them microbiome (Supplementary Table S1). to inhibit DNA repair proteins, further contributing We purchased 96 bacterial strains from the to lasting DNA damage.34–36 Several secreted bacterial reference catalog of the Human Microbiome toxins are known that can bind to receptors or pass Project (HMP, Prof. Dr. Emma Allen-Vercoe through the cell membrane into the cytoplasm. The from the University of Guelph, Canada); 24 bac­ driver bacterium enterotoxigenic B. fragilis secretes teria were kindly provided by Prof. Dr. Cynthia the metalloprotease B. fragilis toxin (BFT) which L. Sears from Johns Hopkins Medical Institutions, leads to E-cadherin cleavage and increased wnt- Baltimore, MD, USA; five strains were purchased signaling in colon epithelial cells and to tumor forma­ from DSMZ (Clostridium septicum (Macé 1889) tion in mice and increased cell proliferation in vivo.­ Ford 1927 DSM7534,56 C. difficile (Hall and 37,38 Bacteria such as Escherichia coli containing the O’Toole 1935) Lawson et al. 2016 DSM27543 pks island are able to produce a genotoxin called (known as Clostridium difficile 63057), colibactin. Upon mucosal breach, colibactin reaches Fusobacterium nucleatum Knorr 1922 the epithelial cells and alkylates DNA, ultimately lead­ DSM15643, Fusobacterium nucleatum subsp. poly­ ing to tumorigenesis.39–41 These examples show that morphum (ex Knorr 1922) Dzink et al. 1990 taxonomically diverse bacteria may lead to the acqui­ DSM20482, and Peptostreptococcus stomatis sition of hallmark capabilities via diverse mechanisms. Downes and Wade 2006 DSM17678); one strain GUT MICROBES e1799733-3 from ATCC (Streptococcus agalactiae To investigate the effect of bacterial surface- ATCC13813); and 31 bacteria were in stock at bound molecules, 145 bacteria were inactivated to the Radboud University Medical Center in allow cellular growth rates to be assessed by mea­ Nijmegen, The Netherlands.58–60 Information suring metabolic activity (see the section “MTT about the bacterial strains, their origin, growth assay” below). Cells of 12 spore-forming bacteria media, and their genome sequence is provided in under our experimental conditions were excluded Supplementary Table S1. from this analysis (see Supplementary Table S1). Bacteria were cultured in their respective media Pelleted bacteria were resuspended in 70% ethanol under anaerobic conditions at 37°C aired with and incubated for 5 min according to our inactiva­ 62 nitrogen gas (N2, see Supplementary Table S1). tion protocol. After centrifugation at 20,000 rcf Alternatively, Ralstonia sp. 5_2_56FAA, Ralstonia for 30 s, bacteria were washed in PBS twice and sp. 5_7_47FAA and Pseudomonas sp. 2_1_26 were inactivated bacteria were frozen at −80°C until grown aerobically at 37°C, and Bacillus smithii was further use. grown anaerobically at its preferred temperature of 50°C. Eight media were prepared to culture bacteria (Supplementary Table S1): (i) brain Culturing of cell lines and identification of their heart infusion-supplemented (BHI-S, ATCC mutational landscapes Medium 1293), (ii) BHI-S supplemented with Five CRC cell lines (Caco-2, HCT15, HCT116, 0.1% Tween 80 at pH 8.0 (BHI-T),61 (iii) HT29, and SW480) and one immortalized embryo­ NADC – 99X medium (ATCC Medium 1804), nic kidney cell line (HEK293T) were selected based (iv) Desulfovibrio medium (ATCC Medium 63 on their differences in mutational landscapes. 2755), (v) Modified Reinforced Clostridial Most commonly mutated oncogenes and tumor Medium (RCM, ATCC Medium 2107), (vi) suppressor genes in CRC were confirmed with tar­ Reinforced Clostridial medium with sodium lac­ geted single molecule molecular inversion probe tate (60% solution) at a concentration of 1.5% 64 (smMIP) mutation analysis as described, with (RCM+, from ATCC Medium 1252), (vii) differ­ additional smMIPs targeting CXCR4 ential RCM (DRCM), and (viii) nutrient broth (NM_001008540.1) codons 281–357, EZH2 (NB, ATCC Medium 3). Bacteria were grown (NM_00004456.4) codons 471–502, 618–645, until the medium was turbid and the optical den­ 679–704, and SF3B1 (NM_012433.2) codons sity (OD) was at least 1.0. Absorbance was 603–471, 833–906 (smMIP sequences are available obtained by measuring OD at 600 nm. upon request), at the Radboud Diagnostics Department, Nijmegen, The Netherlands (Supplementary Table S2). Cells were split twice Obtaining secretomes and bacterial cells a week using Dulbecco’s Modified Eagle Medium To investigate the effect of secreted molecules, we (DMEM, Lonza, Switzerland) supplemented with obtained secretomes from 154 bacterial cultures as 10% fetal bovine serum (FBS, Thermo Fisher follows. After culturing, bacteria were centrifuged Scientific, USA) and 1% Penicillin/Streptomycin at 4,700 rpm for 10 min and some bacteria subse­ (Pen/Strep, Thermo Fisher Scientific, USA). Cells quently at a higher speed to settle them down (see used for this study were not split for more than 25 Supplementary Table S1). Next, supernatants were passages. spun at 4,700 rpm for 10 min to pellet any remain­ For MTT assays, optimal cell seeding in 96 well ing bacteria and filter-sterilized using 0.2 µm filters plates (Greiner Bio-One, Austria) was defined at (Sigma-Aldrich, USA). Molecules larger than 10 5,000 cells/well for Caco-2, 4,000 cells/well for kDa were concentrated using amicon ultra-15 cen­ HCT15, 1,500 cells/well for HCT116, 10,000 cells/ trifugal filters (Merck Millipore, Merck, USA). well for HT29, 6,000 cells/well for SW480, and Concentrated supernatants were frozen at −80°C 20,000 cells/well for HEK293T. Cells were incu­ until further use and are further referred to as bated overnight to attach before the addition of secretomes. secretomes or bacterial cells. e1799733-4 R. TADDESE ET AL.

MTT assay (see Supplementary Tables S3 and S4). To allow comparability between cell lines, normalized Secretomes were diluted to their original concen­ growth rate scores were calculated by dividing per trations in DMEM supplemented with 10% FBS cell line the scores (g) of each of the n bacteria by and 1% Pen/Strep. Inactivated bacteria were diluted the norm (|g|) of the experimental condition with DMEM supplemented with 10% FBS and 1% sffiffiffiffiffiffiffiffiffiffiffi Pn Pen/Strep to an OD of 0.1 and incubated on cell 2 ðjgj ¼ gi ). The normalized growth rate lines up to 72 h. For secretomes, filter-sterilized i¼i bacterial culture media used to generate secretomes scores were used to evaluate whether the enhancing served as a control for cell growth in the assay, or inhibiting effect of a bacteria is significantly while for bacterial cells, DMEM supplemented stronger than the mean effect observed for all with 10% FBS and 1% Pen/Strep served as control other bacteria. For this purpose, growth rate scores for cell growth. MTT assays were performed to were transformed into z-scores and p-values were measure the cell metabolic activity every 24 h. computed by separate one-tailed z-tests for enhan­ These assays involve the conversion of the water- cing or inhibiting effects. Based on these p-values, soluble yellow dye MTT [3-(4,5-dimethylthiazol- strains were identified as enhancers or inhibitors of 2-yl)-2,5-diphenyltetrazolium bromide] to the growth by using a cutoff of p < .05. This cutoff insoluble purple formazan by the action of mito­ represents the 5% extremes of the distribution of chondrial reductase. At 24, 48 and 72 h 10 µl of z-scores and were here used to identify the stron­ MTT (5 mg MTT dissolved per mL PBS) dye was gest effects. The FDR corrected p-values were also added to the wells and cells were incubated for 3 h. reported (Supplementary Tables S3 and S4). Formazan was then solubilized with 150 µL MTT The overall effects of bacterial secretomes and solvent (0.5 mL of 10% Nonidet (dissolved in inactivated cells were visualized by projecting water), 50 mL isopropanol (2-propanol) and their normalized growth scores in a two- 16,7 µL hydrochloric acid fuming 37% together) dimensional space with the t-SNE algorithm.66 To and the concentration determined by optical den­ evaluate if bacteria of the same family have a similar sity at 570 nm (BioRad microplate reader model overall effect on cell growth relative to bacteria 680). Metabolic activity of cell lines was used as from other families, we applied unsupervised near­ 65 a measure for cell growth. All experiments were est neighbor clustering67 and evaluated how often performed in quadruplicate. bacteria from the same family were nearest neigh­ bors compared to a random sample without repla­ cement. For this analysis, we only used bacteria Cell growth analysis from families with more than four representatives. Absorbances at an optical density of 570 nm were Random groups were evaluated per family and measured by MTT assays at four time points (0, 24, were defined to contain the same number of strains 48, and 72 h). Growth rates per hour were calcu­ as the family. Fisher’s exact test was used to evalu­ lated by dividing the difference in absorbance by ate if the nearest neighbor groups were enriched for the time interval between measurements (24 h). bacteria of the same family compared to 1,000 ran­ Results from four independent experimental repli­ dom groups of the same size. The harmonic means cates were averaged. Growth rates between 24 and of p-values from this comparison are reported. 48 h were selected for comparative analysis because that time window captured the optimal growth for most cell lines (Supplementary Figure S1). Association of bacterial virulence genes to growth A growth rate score was defined by subtracting rate changes the growth of negative controls (cells cultured with­ Bacterial genomes were screened for 35 known out bacterial products) from those cultured with virulence genes that may be associated with cancer bacterial products (secretomes or bacterial cells). or epithelial cell changes (Supplementary Table S5). Scores greater than 0 refer to enhanced growth, The virulence factors Map (Mitochondrial asso­ while scores lower than 0 refer to inhibited growth ciated protein), Type-3 secretion system (T3SS) GUT MICROBES e1799733-5 effector protein of Citrobacter rodentium, Shiga subsystem within the random groups are indepen­ toxin 2A (Stx2A), Shigella enterotoxin 1 (ShEt1), dent; (ii) Counts are expressed as averages from and colibactin (cyclomodulin toxin on polyketide many random samples; (iii) the mean and variance synthase (pks) island of Enterobacteriaceae) were are equivalent, all features consistent with a Poisson identified in the Enterobacteriaceae family, distribution.70 B. fragilis toxin (BFT) in B. fragilis species, and FadA in the Fusobacteriaceae family (Supplementary Table S5). Clostridium difficile Results toxin A, and B (TcdA/TcdB) in Clostridioides diffi­ Reproducibility of growth rate alterations by cile (Prévot 1938) Lawson et al. 2016, and Alpha- bacterial cells and secretomes toxin of Clostridium septicum (Mace 1889) Ford 1927 were identified as secreted factors in previous To identify alterations in the growth rates of CRC reports.56,57,68 Growth rate changes of strains con­ cell lines by bacterial cells or their secreted pro­ taining virulence genes (if present in ≥2 strains) ducts, inactivated cells or secretomes were added were compared to those of their non-virulent coun­ to five CRC cell lines with different mutational terparts within the order (Clostridiales), family landscapes and one embryonic kidney cell line (Fusobacteriaceae and Enterobacteriaceae) or spe­ HEK293T (see Methods and Supplementary Table cies (B. fragilis). Groups were compared using S2). HEK293T cells are immortalized by DNA of Mann-Whitney U-test of aggregate data of all cell human adenovirus type 5 resulting in senescence of 71 lines. P < .05 was considered significant. the pRb and p53 pathway. While these cells are not normal, they have no mutations in the genes that are commonly mutated in CRC, as confirmed Genes and subsystems identification by our smMIP analysis (Supplemental Table 2). For To identify genes that are associated with the inhi­ each cell line independently, plain cell culture and biting/enhancing effects of bacterial strains within bacterial culture media served as a control for cell families, we sorted all strains based on their effect growth for cells and secretomes, respectively. on growth rate scores and used a normalized A total of 7,176 experiments were conducted Kolmogorov–Smirnov statistic to quantify the asso­ where we measured the bacterial effect on cell ciation of a gene with the observed effect. The growth. Each experiment was repeated four times. significance of the rank-based statistic was esti­ We evaluated the reproducibility of these replicates mated by comparing its value to values obtained by performing linear regression over all pairwise from 103 random permutations of the same list. combinations of replicates, i.e. measurements for This provided all genes encoded by the genomes all the possible combinations of two replicates for from a family with a p-value which quantified the every strain appended into two separate lists. As association of the gene to the inhibiting/enhancing shown in Supplementary Figure S2, we found high effect.We evaluated if genes that belong to the same reproducibility between replicates (regression coef­ functional subsystems42,69 were more often found ficient:0.87 ± 0.05, intercept: 0.04 ± 0.02). Based on to be significantly associated with the inhibiting/ this reproducibility, we averaged the four experi­ enhancing effect than to 103 random groups of mental replicates for further analysis. genes. We defined this association by modeling the average count of genes belonging to Contrasting effects between bacterial cells and a functional subsystem within the random groups secretomes as Poisson distributed variables. We then tested if the count of genes with significant p-values was Figure 1(a) summarizes the effect of bacterial cells statistically higher than expected from the Poisson and secretomes on the growth of human cell lines. model, with a significance level of 0.05 after Overall, bacterial cells exhibit a stronger inhibiting Benjamini/Hochberg correction for multiple tests. effect than secretomes (p = 1.02e-75, Wilcoxon We used the Poisson distribution as the null dis­ signed rank test, Figure 1(b)). There was a low tribution since (i) the labels for functional correlation between the overall effects of e1799733-6 R. TADDESE ET AL.

Figure 1. Growth rate scores of six human cell lines upon treatment with bacterial cells and secretomes. (a) Heatmap indicating low and high growth rate scores, respectively red and blue. Bacteria are sorted within bacterial families by the average growth rate score. Red numbered octagons highlight the strains discussed in the text: Bacteroides sp. 2_1_22 (1), B. fragilis K570 clinda R (ETBF) (2), B. sp. 4_1_36 (3), Clostridium septicum (Mace 1889) Ford 1927 (4), C. sp. D5 (5), Escherichia coli D9 (6), Klebsiella sp. 1_1_55 (7), E. coli 4_1_47FAA (8), F. nucleatum DSM 15643 (ATCC 25586) (9), F. nucleatum DSM 20482 (ATCC 10953) (10), F. necrophorum subsp. funduliforme 1_1_36S (11), F. nucleatum subsp. animalis 11_3_2 (12), Lachnospiraceae bacterium 8_1_57FAA (13), L. bacterium 3_1_46FAA (14), Streptococcus bovis 1212 (15), S. bovis 1459 (16), S. bovis 1417 (17), S. bovis 207 (18), Pediococcus acidilactici 7_4 (19), Pseudomonas sp. 2_1_26 (20), D. sp. 6_1_46AFAA (21), Ralstonia sp. 5_2_56FAA (22), Ruminococcaceae bacterium D16 (23), GUT MICROBES e1799733-7

Synergistes sp. 3_1_syn1 (24), Desulfovibrio sp. 3_1_syn3 (25), Propionibacterium sp. 5_U_42AFAA (26), and Eubacterium sp. 3_1_31 (27). Highlighted with asterisks are cases that correspond to the 5% extremes of the z-score distribution. (b) Distribution of the growth rate scores for bacterial cells and secretomes. Histograms show the distribution of the values from the two heatmaps above, indicating that on average bacterial cells exhibit a stronger inhibiting effect when compared to secretomes. secretomes and inactivated bacteria on cell growth Difference in growth rate alterations between CRC (Pearson r = 0.176). A low correlation was also cell lines observed when the measurements were stratified Growth rates were significantly enhanced or inhib­ per bacterial family (Supplementary Table S6), ited (p < .05) in one or more cell lines in 35 out of indicating that specific factors within the two com­ 145 (24.1%) inactivated bacterial strains (Figure 2 partments (cell wall attached or secreted molecules) (a), Supplementary Table S3) and 33 out of 154 are of importance for the observed effects. (21.4%) secretomes (Figure 2(b), Supplementary

Figure 2. Growth rate alterations of cells lines upon incubation with bacterial cells and secretomes. Distribution plots illustrating effects of (a) bacterial cells and (b) secretomes on cell lines. Negative numbers indicate growth inhibition whereas positive numbers show growth enhancement. The color intensity of the circles represents significance of the effect on growth. (c) Overview of the number of bacterial cells and secretomes significantly enhancing or inhibiting cell growth per tested cell line, sorted by bacterial family. The shading of the bar (arrow pointing upwards) highlights enhancing and unshaded bar (arrow pointing downwards) highlights inhibiting strains. (d) Correlation of number of strains significantly altering growth rates to the number of pathogenic mutations present in cell lines. HEK293T, Caco-2, HT29, SW480, HCT116, and HCT15 were shown to possess 0, 1, 2, 2, 3, and 4 pathogenic mutations, respectively. e1799733-8 R. TADDESE ET AL.

Table S4). Growth rates of HEK293T cells were and 1417) and one inactivated bacterium (strain affected by the lowest number of bacteria (n = 21, 1459) selectively enhanced growth in HT29 cells, n = 3 enhanced and n = 18 inhibited growth). On while no effects were observed in other cell lines the other end of the spectrum were HCT116 cells (Figures 1 and 2(c)). The genomes of these enhan­ that were affected by 28 different bacteria (n = 11 cing Streptococcus bovis strains cluster together in enhanced and n = 17 inhibited growth) and HCT15 a phylogenetic tree with Streptococcus gallolyticus cells that were affected by 27 different bacteria subsp. gallolyticus (SGG) and subsp. pasteurianus (n = 8 enhanced and n = 19 inhibited; Figure 2 (SGP) (Supplementary Figure 3). Other notable (c)). These two cell lines had microsatellite instabil­ cell-line specific effects include Erysipelotrichaceae ity (MSI) and harbored the greatest number of cells, and Tannerellaceae secretomes that signifi­ pathogenic mutations in known tumor suppressor cantly enhance the growth of HCT15 and and oncogenes (n = 3 and n = 4, respectively, see HCT116 cells, respectively. Supplementary Table S2). In general, the number of pathogenic mutations of a cell line correlated with the number of bacteria that significantly affected its Bacterial family-level and strain-level effects on cell growth (Pearson r = 0.931, p < .01, see Figure 2(d)), growth rates suggesting that acquiring hallmark mutations To assess the overall effect of the different bacterial might make cells more susceptible to growth rate secretomes and cells on our six cell lines, we pro­ changes by bacteria. jected the growth rate scores into a two- Some strains significantly enhanced or inhibited dimensional t-SNE plot. Figure 3 shows this lower the growth rate of specific cell lines (Figure 1). dimensional space overlayed with family-specific Streptococcaceae cells generally had a neutral effect colors and a shade corresponding to the average on cell growth, however, some Streptococcaceae growth effect. We observed a clear clustering of secretomes specifically enhanced the growth of most, but not all of the bacterial families, i.e. cells HT29 and SW480 cells (Figure 1). Three or secretomes from the same families tend to have Streptococcus bovis secretomes (strains 207, 1212 similar effects on the different cell lines (see also

Figure 3. T-SNE plots summarizing the overall growth effects of bacterial cells (a) and secretomes (b) on six human cell lines. Colored circles correspond to strains belonging to particular bacterial families. Magenta and light blue shading around the circles indicate enhancing and inhibiting effects of strains, respectively. Families labeled as “Others” contains the following strains for bacterial cells (A): Lactobacillaceae (1), Peptostreptococcaceae (2), Desulfovibrionaceae (3), Eubacteriaceae (4), Bifidobacteriaceae (5), Enterococcaceae (6), Veillonellaceae (7), Synergistaceae (8), Burkholderiaceae (9), Pseudomonadaceae (10), Propionibacteriaceae (11), Ruminococcaceae (12), Akkermansiaceae (13), Acidaminococcaceae (14). And the following strains for secretomes (B): Lactobacillaceae (1), Eubacteriaceae (2), Clostridiaceae (3), Peptostreptococcaceae (4), Bifidobacteriaceae (5), Enterococcaceae (6), Veillonellaceae (7), Synergistaceae (8), Burkholderiaceae (9), Desulfovibrionaceae (10), Propionibacteriaceae (11), Ruminococcaceae (12), Pseudomonadaceae (13), Akkermansiaceae (14), Acidaminococcaceae (15), Bacillaceae (16). GUT MICROBES e1799733-9

Table 1. Secretomes and bacteria significantly enhancing or reducing cell growth rate (z-scores).

(Continued) e1799733-10 R. TADDESE ET AL.

Table 1. (Continued).

Secretomes are highlighted in gray, green represents significant enhancement (p < 0.05) in cell growth rate and red represents significant reduction (p < 0.05) in cell growth rate.

Figure 1 and Table 1). To confirm this observation, 1). Contrastingly, Clostridiaceae secretomes gener­ we tested if the growth effects of bacteria from the ally inhibited growth rates. same family were more similar than one would In the Bacteroidaceae family (n = 41 strains expect by chance by permuting the data labels tested), secretomes and bacterial cells of seven and 1,000 times (see Methods). The effect of bacterial one strains significantly enhanced cell growth, cells and secretomes was found to be significantly respectively. The effects were most prominently clustered for five and three bacterial families, observed in Caco-2 cells, while the growth of respectively (Supplementary Table S7). For bacter­ HEK293T cells was only significantly enhanced by ial cells, the most striking effect was observed for the secretome of Bacteroides sp. 4_1_36 (Figure 2 Fusobacteriaceae that generally inhibited cell (c) and Table 1). Only three Enterobacteriaceae growth. Most Bacteroidaceae, Enterobacteriaceae, secretomes (n = 15) significantly enhanced the and Erysipelotrichaceae secretomes enhanced cell growth of HEK293T cells (Escherichia coli growth, although not always significantly (Figure 4_1_47FAA) and HCT116 (Escherichia coli GUT MICROBES e1799733-11

4_1_47FAA and D9, and Klebsiella sp. 1_1_55) status, since most secretomes that inhibited while no effects were observed for bacterial cells. HCT116, SW480 and HCT15, did not inhibit the Growth-inhibiting effects were mainly observed growth of Caco-2 and HEK293 T cells. within the family Fusobacteriaceae (Figure 1 and Table 1). From the 12 out of 16 significant Fusobacteriaceae (81.3%) cells, 2 enhanced and 10 Families with fewer than 5 strains tested inhibited cellular growth. Fusobacterium necro­ Among strains from families with less than five tested phorum subsp. funduliforme 1_1_36S cells strains (n = 18), Eubacterium sp. 3_1_31 and enhanced growth in HCT116, SW480, and Propionibacterium sp. 5_U_42AFAA cells increased HEK293T cells. Strikingly, while Fusobacterium cell growth rates in SW480 and HCT15 cells, respec­ nucleatum subsp. animalis 11_3_2 cells enhanced tively (Table 1). Interestingly, Pseudomonas sp. the growth of Caco-2 and HCT116, its secretome 2_1_26 secretomes significantly inhibited the growth inhibited growth in those same cell lines. Especially rates of all cell lines while the cells specifically inhib­ the cell line HCT15 was sensitive to ited SW480. Pediococcus acidilactici 7_4 and Fusobacteriaceae growth inhibition where 11 out Ruminococcaceae bacterium D16 cells selectively of 16 strains significantly reduced growth rates. inhibited HEK293T, while Synergistes sp. 3_1_syn1 Alternatively, HEK293T and Caco-2 were less sen­ also inhibited HCT116. Aerobically cultured sitive to Fusobacteriaceae with only four out of 16 Ralstonia sp. 5_2_56FAA secretomes inhibited 2 cell strains inhibiting cell growth. Notably, the effect of lines, SW480 and HEK293T. For Desulfovibrio sp. Fusobacteriaceae secretomes on cell growth may be 3_1_syn3, the secretome increased Caco-2 growth cell-specific depending on, for example, mutation while the bacterial cells increased HT29 growth.

Figure 4. Influence of strains with and without encoded virulence factors on cellular growth rates. B. fragilis (a), Fusobacteriaceae (b), Enterobacteriaceae (c) and Clostridiales (d) encoding the virulence factors bft, fadA, any toxin (Map, pks, ShEt1, Stx2A), and any toxin (TcdA, TcdB, alpha-toxin), respectively, were compared to strains without these encoded virulence factors (Mann-Whitney U test). A trend toward cell growth enhancement was observed for B. fragilis bft+ secretomes (p = .07) (A), while significant inhibition of cell growth was observed for fadA+ Fusobacteriaceae cells (p < .0001), and secretomes (p < .05) (B), for Enterobacteriaceae secretomes encoding toxins (p < .0001) (C), and for Clostridiales secretomes encoding toxins (p < .0001) (D). e1799733-12 R. TADDESE ET AL.

Contrastingly, these same bacterial cells decreased the The presence of virulence genes is associated with growth of HCT116 and HEK293T. Similarly, growth rate inhibition Desulfovibrio sp. 6_1_46AFAA cells decreased the To explain the complex, sometimes strain- growth rates of HCT116, SW480 and HEK293T cells. dependent patterns of growth enhancement or inhibition, we analyzed the genome sequences of 144/157 tested gut bacteria. First, we checked Strain-specific effects that contrast their family whether 35 known bacterial family-specific viru­ While strains from the same bacterial families tend to lence genes were present within the genomes of have similar effects on the growth rates of cell lines the tested strains (Supplementary Table S9), (Supplementary Table S7), large variations were because some of the encoded virulence factors observed within certain families. For instance, within have been linked to cell proliferation changes. the Clostridiaceae family, the secretome of Clostridium Nine toxin genes were found, including TcdA, septicum (Mace 1889) Ford 1927 strongly inhibited TcdB,72 alpha-toxin68 of Clostridiales; FadA;31 coli­ the growth of all tested cell lines, while the Clostridium bactin present on the pks-island;73,74 Shiga toxin sp. D5 secretome enhanced growth, although the sig­ ShEt1; Shigella enterotoxin Stx2A; effector protein nificance threshold was not reached (Figure 1 and Map secreted by T3SS of Citrobacter rodentium and Supplementary Table S4). Similarly, Bacteroides sp. Escherichia coli;75,76 and BFT.38 2_1_22 cells strongly inhibited the growth rates of all As shown in Figure 4, strains containing viru­ cell lines while B. fragilis K570 cells enhanced growth lence genes tend to change growth rates, relative in most cell lines (Figure 1 and Supplementary Table to related strains without those virulence genes. S3). A large growth rate variation was also observed in For example, the secretomes of Clostridiales cell lines exposed to Lachnospiraceae cells (n = 11). For strains significantly inhibited growth rate if this family, the cells of L. bacterium 3_1_46FAA and their genomes contained TcdA, TcdB or alpha- L. bacterium 8_1_57FAA significantly inhibited the toxin (Figure 4(a), p < .0001). TcdA and TcdB growth rates of all cell lines, while most of the other secretion by Clostridioides difficile (Prévot 1938) strains showed weak or low inhibition. Lawson et al. 2016 was confirmed by ELISA The observed variations in growth effect within (data not shown). Similarly, Fusobacteria strains bacterial families might either be explained by the encoding the membrane protein FadA, which phylogenetic distances between the strains or by char­ might be responsible for growth rate changes acteristics with a non-phylogenetic distribution, such of epithelial cells,31 inhibited growth rates sig­ as accessory functions. To evaluate this, we measured nificantly (Figure 4(b), p < .0001 and p < .05 for the distances on a phylogenomic tree and compared bacterial cells and secretomes, respectively). them with the differences in growth rate effects over Within the Enterobacteriaceae family, multiple the cell lines. For most bacterial families, there is no secreted toxins were identified in the genomes, association between the growth rate effects and phy­ including colibactin, ShEt1, Stx2A, and Map. logenetic distances (Supplementary Table S8, Secretomes of Enterobacteriaceae possessing any Supplementary Figure S4), suggesting that these of these toxins inhibited cell growth relative to effects may be associated with accessory functions strains without these toxins (Figure 4(c), that are independently gained or lost in different p < .0001). No differences were observed lineages. For Erysipelotrichaceae secretomes and cells, between bacterial cells of Enterobacteriaceae Fusobacteriaceae cells, and Lachnospiraceae secre­ with or without the toxin genes. The secretomes tomes, we found that the phylogenetic distance was of three B. fragilis strains encoding the secreted significantly correlated with the growth rate effects, enterotoxin bft enhanced the growth rates of suggesting that these effects may be associated to CRC cells, while the five B. fragilis strains with­ variations in universally shared genes or to accessory out the toxin did not, although this trend was functions with phylogenetically consistent dynamics. not significant (Figure 4(a), p = .075). The trend GUT MICROBES e1799733-13 was not observed for bacterial cells, where only HCT116, SW480, and HCT15) with different B. fragilis K570 significantly enhanced growth mutation landscapes representing commonly rates (Table 1). mutated genes in CRC, and one immortalized kidney cell line (HEK293T). Our results show that cell growth enhancing and inhibiting effects Functional categories associated with differential of gut bacteria depend both on the mutational effects within families landscape of the cells and on the identity and Besides the toxin genes described above, other genes functional content of the bacteria, including might also play a role in the observed effects. Thus, secreted or cell wall attached factors. CRC is we next performed an unbiased comparative gen­ a heterogeneous disease, as is reflected in the five ome analysis where we associated all annotated bac­ different CRC cell lines with mutations in key terial genes to the effect of the strain on cell growth. CRC related genes (KRAS, APC, BRAF, TP53, We next grouped the genes by functional category CTNNB1, and PIK3CA). These mutations are and assessed whether genes within a category were absent from the HEK293T cells, an immortalized significantly associated with cell growth alterations. kidney cell line that was transformed by DNA of Based on the PATRIC42 annotations we evaluated a human adenovirus, causing senescence in the genes in two hierarchical levels of functions, namely pRb and p53 pathway.71 HEK293T cells were ‘Subsystems’ and ‘Superclass’. All functional cate­ affected by the lowest number of gut bacterial gories found to be significantly associated with cell strains, with only small differences. growth alterations are listed in Supplementary Table S10. Closely related bacteria may have distinct effects on The “Membrane transport” superclass was signif­ cell growth icantly associated with inhibiting Enterobacteriaceae cells and secretomes, and with enhancing A striking observation was that the effects of bacterial Fusobacteriaceae secretomes. Other enriched super­ cells and secretomes were strongly associated with bac­ classes included “Cell envelope”, “Metabolism”, terial families, although exceptions to this general pat­ “Cellular processes”, “Protein processing”, tern were observed. Previous studies have found that “Energy”, and “Stress response, defense and viru­ Fusobacteria, Streptococcus, Peptostreptococcus, lence” (Supplementary Table S10). Subsystems Ruminococcus, and Escherichia/Shigella tend to be including “Cobalamin synthesis”, “Ethanolamine enriched in tumors, while Bacteroides, Pseudomonas, utilization”, and the “Dpp dipeptide ABC transport Lachnospira, and Anaerostipes are depleted.5,7,9,22- system” were consistently found to be associated 24,28,31,41,77-80 Regardless of the enrichment or depletion with growth enhancement or inhibition in multiple on CRC tumors in vivo, our in vitro results indicate that bacterial families and in multiple cell lines closely related bacteria may have distinct effects on cell (Supplementary Table S10). The significant effects growth. For example, we observed that different of other subsystems including “Vir-like type 4 secre­ Fusobacteria strains, which were all cultured in the tion system”, “Glutamate fermentation”, same media under the same conditions, may have “Flagellum”, “Branched-chain amino acid biosynth­ opposing effects on cell growth, while these bacteria esis”, and others were associated with specific bac­ are consistently enriched in patients.24,28,81 This sug­ terial families. We expect that these statistical gests that specific bacterial factors may play a role. associations will provide valuable leads for future experiments. Fusobacteriaceae: enhancing or inhibiting growth? Previous studies indicated that Fusobacteriaceae Discussion enhanced the growth of HCT116, SW480, and HT29 Over 150 human gut bacteria belonging to taxo­ cells.31,80 F. nucleatum ATCC25586 was shown to nomic groups that have previously been associated enhance CRC cell growth via interaction with Toll- with CRC were tested for their effects on cell like receptors TLR4, TLR2, and myeloid differentiation growth of five CRC cell lines (HT29, Caco-2, primary response protein 88 (MYD88),80 and the e1799733-14 R. TADDESE ET AL.

F. nucleatum strain Fn12230 was previously shown to relative to non-toxigenic Enterobacteriaceae strains. enhance cell growth through the cell-wall attached Colibactin (present in four of our Escherichia strains) adhesin FadA.31 Our results showed that most is a genotoxic compound that alkylates DNA and gen­ Fusobacteriaceae significantly inhibited cellular growth, erates DNA double-strand breaks.41,78 The DNA dama­ including Fusobacterium nucleatum ATCC25586, con­ ging effect of colibactin may not directly affect cell trasting previous observations,72,80 and that the pre­ growth in our experimental setup, although colibactin sence of the FadA gene was significantly linked to may induce cell cycle arrest via SUMOylation of TP53 growth inhibition by cells and secretomes (Table 1). causing inactivation.73,74 Cell cycle arrest would stall cell Notably, the secretomes showed less pronounced inhi­ growth, which can only happen in TP53 wild-type cell bition than bacterial cells. While FadA is membrane- lines with active TP53 protein. Indeed, the only cell bound, secretomes likely include outer membrane vesi­ lines that were relatively inhibited by strains encoding cles (OMVs) that are 40–110 nm in size and express colibactin were the wildtype TP53 cell lines HEK293T FadA.32,82 To rule out the possibility that these con­ and HCT116. trasting results were due to differences in methods, we An important virulence factor of B. fragilis is BFT.84 compared our high-throughput MTT-based assay, While in previous research, BFT was shown to enhance used in this study, with the cell counting assay, that cell growth of HT29/c1 cells via β-catenin nuclear was employed in the referred studies, on six cell lines, signaling,38 enterotoxigenic B. fragilis secretomes using six different secretomes, and found a high corre­ (VPI13784 (bft1), 86–5443-2-2 (bft2), and K570 lation (Pearson’s r = 0.813, Supplementary Figure S5). (bft3)) only marginally enhanced cell growth in our These results confirm that the observed inhibitory assay compared to the other B. fragilis secretomes in effects by Fusobacteriaceae strains do not depend on our screen. The mild effectsas observed may depend on the applied experimental techniques, but may partly be the level of toxin production and secretion under our due to the use of different Fusobacteriaceae strains experimental conditions. Interestingly, enterotoxigenic (Fn12230, ATCC25586, ATCC23726) isolated from B. fragilis str. Korea 570 cells significantly enhanced extra-intestinal sites.83 Specifically, HCT15 cell growth growth, which might be independent of BFT and was significantly inhibited by 11/16 Fusobacteriaceae related to other cell-wall-attached factors. strains (nine cells and three secretomes). HCT15 cells contain a missense mutation in MYD88 (p.Arg264Ter) Streptococcus bovis strains specifically enhance resulting in an MYD88 deficiency, and may thus growth of HT29 cells explain the insensitivity of this cell line to F. nucleatum subsp. animalis 11_3_2 and Streptococcus bovis infections have been linked F. necrophorum subsp. funduliforme 1_1_36S, the two to colorectal neoplasia.43,85,86 Our results Fusobacteriaceae strains that promoted the growth of demonstrate that secretomes of Streptococcus the other cell lines, but not of HCT15. bovis strains that are closely related to known S. gallolyticus and S. pasteurianus strains (Supplementary Figure S3), selectively enhance Virulence factors are associated to cell growth the growth of HT29 cells. This is in line with inhibition a previous study showing cell growth enhancing The growth-inhibiting properties of Clostridiaceae effects in HT29 and HCT116 cells that were secretomes may result from toxins encoded by this mediated through β-catenin, while no effect was family. We observed that Clostridioides difficile (Prévot observed in SW480 and HEK293T cells.87 An 1938) Lawson et al. 2016 and Clostridium septicum intact β-catenin pathway may, therefore, be (Mace 1889) Ford 1927 secreting the virulence factors required to observe the specific effect of TcdA and TcdB, and lethal alpha toxin, respectively, S. gallolyticus on cell growth as is the case in significantly inhibited cell growth compared to the HT29 cells,88 which may thus be sensitive to the other Clostridiales secretomes. Clostridium septicum effects of S. gallolyticus in our assay. HCT116 has been associated with CRC in the past.14,15 cells have a mutation in CTNNB1 (p.Ser45del) Enterobacteriaceae strains encoding the toxins coli­ that interferes with β-catenin degradation, which bactin, Stx2A, ShEt1, and Map inhibited cell growth may explain its insensitivity to S. gallolyticus. GUT MICROBES e1799733-15

Alternatively, mutations in the APC-gene in the surface-exposed lipoproteins with high affinity for other CRC-cells89 may interfere with β-catenin cobalamin.93 Such molecules may remove cobalamin signaling depending on the specific mutation. directly from the media, making it unavailable to the human cells and impeding their growth. The “Ethanolamine utilization” pathway was Bacterial functions associated with cell growth another metabolic process that we found to be asso­ alterations ciated with the inhibiting effectof Fusobacteriaceae cells Several functional categories were significantly asso­ on the growth rate of CRC cell lines. Ethanolamine ciated with cell growth. Most of these functions were (EA) is the basal component of phosphatidylethanola­ identified in specific bacterial families and consistently mine, a major phospholipid in animal cell membranes inhibited or enhanced cell growth in different cell lines. and is utilized by bacteria including Fusobacteria as These functions may reflect novel pathways of bacterial a carbon source in the gut.94–96 EA sensing regulators interference with cell growth which, to our knowledge, have been proposed to regulate virulence in have not been previously identified. Most functions are Enterobacteriaceae.96,97 It remains to be tested if the related to cell metabolism, secretion, and transport EA in human cell membranes triggers virulence factors systems. For example, secretomes of in Fusobacteria that encode EA utilization genes, or Enterobacteriaceae that encode the “Vir-like type 4 perhaps if inactivated Fusobacteria cells retain the capa­ secretion system” inhibited the growth of all cell lines. city to digest and kill human cells by the activity of EA Similarly, the gene superclass “Membrane transport” utilization enzymes. was mostly associated with secretomes that inhibited Overall, the statistical associations found in this cell growth (Supplementary Table S10). Molecules that exploratory analysis provide valuable clues about the are secreted by these bacterial transport systems may be possible functions and mechanisms that drive the inter­ responsible for the inhibiting effect. For example, the actions of bacteria with human cells in the gut. Future Vir-like type 4 secretion system allows bacteria to experiments are needed to confirm whether these fac­ secrete proteinaceous effectors that kill competitors.90 tors are causal and to further clarify the molecular Here, we report an important first step in understand­ mechanisms involved. ing the cell growth enhancing or inhibiting effects of human gut bacteria by identifying putative transport Outlook systems for effector molecules. While the growth effects of secretomes were mostly Our broad screen revealed many significant associa­ associated with membrane transport functions, effects tions between gut bacteria, their encoded functions, on cell growth by bacterial cells were associated with and growth enhancement or inhibition of human cell metabolic pathways (Supplementary Table S10). It is lines. Many growth rate effects remain elusive and need possible that these associations may be attributed to to be further examined, such as their specificity for metabolic enzymes that may still be, although the bac­ CRC. Moreover, it will be important to investigate the terial cells were inactivated. In other ecosystems, meta­ growth rate effects of living bacterial communities or bolic enzymes of dead bacteria have been shown to mock communities, which are thought to synergize in remain active for up to 96 h.91 Our experiment was affecting tumorigenesis,53 but fall outside the scope of performed within 72 h. The synthesis of cobalamin our present study. Bacterial effects should be examined (vitamin B12), which is important for human cell pro­ in more natural environments that mimic the condi­ liferation in vitro92 and a common addition to cell tions in the human gut, e.g. in co-culture with mucus, culturing media, was significantly associated with the immune cells, and/or within organoid cultures.98 Our cell growth enhancing effect of Bacteroidaceae and study forms an important baseline for such further Enterobacteriaceae cells. Several possible scenarios can research by identifying important traits in individual be envisioned to explain this observation. First, it bacterial strains that are associated with enhancing or remains to be tested whether vitamin B12 was retained inhibiting cell growth, as well as important host factors in the bacterial fraction after washing, stimulating that determine sensitivity to those bacterial traits. The human cell growth on those cells. Second, different influence of individual bacterial traits should be the human gut-associated Bacteroides strains contain focus of follow-up research and can be investigated e1799733-16 R. TADDESE ET AL. with add-back experiments, by introducing, e.g. viru­ (NWO) Vidi grant 864.14.004. AB was supported by NWO lence genes in non-virulent strains. Veni grant 016.166.089.

Conclusions ORCID

Above, we presented the results of the first large-scale Rahwa Taddese http://orcid.org/0000-0002-4516-6050 analysis of the effects of gut bacteria on CRC cell Daniel R. Garza http://orcid.org/0000-0003-3865-2146 growth. Our results with bacterial cells and secretomes Marien I. de Jonge http://orcid.org/0000-0003-2812-5895 reflect the complexity of the microbe–host interactions Clara Belzer http://orcid.org/0000-0001-6922-836X Steven Aalvink http://orcid.org/0000-0001-7554-1723 in the human gut. First, bacterial families tend to have Iris D. Nagtegaal http://orcid.org/0000-0003-0887-4127 consistent effects on cell growth, although these effects Annemarie Boleij http://orcid.org/0000-0003-4495-5880 are not universal. This may partially be explained by the presence of virulence genes in some strains. Second, there are cell line dependent effects in cells due to their References mutational landscape heterogeneity. Notably, these cell 1. Sender R, Fuchs S, Milo R. Revised estimates for the lines have acquired several different cancer hallmarks, number of human and bacteria cells in the body. PLoS yet their growth can still be influenced by specific Biol. 2016;14:e1002533–e. doi:10.1371/journal.pbio.10 bacteria. Our results suggest that the response of epithe­ 02533. lial cells to gut bacteria may differ between patients due 2. Rajilić-Stojanović M, de Vos WM. The first 1000 cul­ to differences in their gut bacteria. The relevance of our tured species of the human gastrointestinal microbiota. FEMS Microbiol Rev. 2014;38:996–1047. doi:10.1111/ in vitro results for patients and CRC specificity remains 1574-6976.12075. to be studied. Cell growth enhancing and inhibiting 3. Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, bacterial traits could be important for determining Manichanh C, Nielsen T, Pons N, Levenez F, Yamada risk for cancer or its progression, and these conse­ T, et al. A human gut microbial gene catalogue estab­ quences could potentially be counteracted by micro­ lished by metagenomic sequencing. Nature. biome modulation. Currently, microbiome medicine 2010;464:59–65. doi:10.1038/nature08821. 4. Arnold M, Sierra MS, Laversanne M, Soerjomataram I, applications have already been adapted to some other Jemal A, Bray F. Global patterns and trends in colorectal diseases. For instance, Akkermansia muciniphila was cancer incidence and mortality. Gut. 2017;66:683–691. demonstrated to improve diabetes type 2 and obesity doi:10.1136/gutjnl-2015-310912. in mice.17,18 Resistant life-threatening Clostridium diffi­ 5. Gao R, Kong C, Huang L, Li H, Qu X, Liu Z, Lan P, cile infections and ulcerative colitis were successfully Wang J, Qin H. Mucosa-associated microbiota signa­ treated with fecal microbiota transplants (FMT).19,20 ture in colorectal cancer. Eur J Clin Microbiol Infect Dis Off Publ Eur Soc Clin Microbiol. 2017;36:2073–2083. Our study highlights the complex processes at play at doi:10.1007/s10096-017-3026-4. the gut–microbiome interface and contributes to 6. Tjalsma H, Boleij A, Marchesi JR, Dutilh BE. A bacterial a better understanding of the role of different bacterial driver-passenger model for colorectal cancer: beyond strains in altering colonic epithelial cell proliferation. the usual suspects. Nat Rev Microbiol. 2012;10:575–582. doi:10.1038/nrmicro2819. 7. Gao Z, Guo B, Gao R, Zhu Q, Qin H. Microbiota Acknowledgments disbiosis is associated with colorectal cancer. Front Microbiol. 2015;6:20. doi:10.3389/fmicb.2015.00020. We thank Shaoguang Wu and Cynthia Sears from Johns 8. Hanahan D, Weinberg RA. Hallmarks of cancer: the Hopkins Medical Institutions for providing different gut bac­ next generation. Cell. 2011;144:646–674. doi:10.1016/j. terial strains (see Methods). cell.2011.02.013. 9. Marchesi JR, Dutilh BE, Hall N, Peters WHM, Roelofs R, Boleij A, Tjalsma H. Towards the human colorectal Funding cancer microbiome. PloS One. 2011;6:e20447–e. doi:10.1371/journal.pone.0020447. This work was supported by the Dutch Cancer Society (KWF; 10. Wirbel J, Pyl PT, Kartal E, Zych K, Kashani A, Milanese KUN 2015-7739). RT was supported by RIMLS grant 014-058. A, Fleck JS, Voigt AY, Palleja A, Ponnudurai R, et al. DRG was supported by CNPQ/BRASIL. BED was supported Meta-analysis of fecal metagenomes reveals global by the Netherlands Organization for Scientific Research microbial signatures that are specific for colorectal GUT MICROBES e1799733-17

cancer. Nat Med. 2019;25:679–689. doi:10.1038/s41591- colorectal cancer patients and healthy volunteers. Isme J. 019-0406-6. 2012;6:320–329. doi:10.1038/ismej.2011.109. 11. Xu K, Jiang B. Analysis of Mucosa-associated microbiota in 26. Hale VL, Jeraldo P, Mundy M, Yao J, Keeney G, Scott N, colorectal cancer. Med Sci Monit Int Med J Exp Clin Res. Cheek EH, Davidson J, Greene M, Martinez C, et al. 2017;23:4422–4430. doi:10.12659/MSM.904220. Synthesis of multi-omic data and community metabolic 12. Donia MS. A toolbox for microbiome engineering. Cell models reveals insights into the role of hydrogen sulfide Syst. 2015;1:21–23. doi:10.1016/j.cels.2015.07.003. in colon cancer. Methods (San Diego, Calif). 13. Foo JL, Ling H, Lee YS, Chang MW. Microbiome engi­ 2018;149:59–68. doi:10.1016/j.ymeth.2018.04.024. neering: current applications and its future. Biotechnol 27. Boleij A, Hechenbleikner EM, Goodwin AC, Badani R, J. 2017;12. doi:10.1002/biot.201600099. Stein EM, Lazarev MG, Ellis B, Carroll KC, Albesiano E, 14. Garcia-Jimenez B, de la Rosa T, Wilkinson MD. Wick EC, et al. The Bacteroides fragilis toxin gene is MDPbiome: microbiome engineering through prescrip­ prevalent in the colon mucosa of colorectal cancer tive perturbations. Bioinformatics (Oxford, England). patients. Clin Infect Dis Offl Publ Infect Dis Soc Am. 2018;34:i838–i47. doi:10.1093/bioinformatics/bty562. 2015;60:208–215. doi:10.1093/cid/ciu787. 15. Sonnenburg JL. Microbiome engineering. Nature. 28. Kostic AD, Gevers D, Pedamallu CS, Michaud M, Duke 2015;518:S10. doi:10.1038/518S10a. F, Earl AM, Ojesina AI, Jung J, Bass AJ, Tabernero J, et 16. Bernardes N, Seruca R, Chakrabarty AM, Fialho AM. al. Genomic analysis identifies association of Microbial-based therapy of cancer: current progress and Fusobacterium with colorectal carcinoma. Genome future prospects. Bioeng Bugs. 2010;1:178–190. Res. 2012;22:292–298. doi:10.1101/gr.126573.111. doi:10.4161/bbug.1.3.10903. 29. Boleij A, Dutilh BE, Kortman GA, Roelofs R, Laarakkers 17. Song S, Vuai MS, Zhong M. The role of bacteria in cancer CM, Engelke UF, Tjalsma H. Bacterial responses to therapy - enemies in the past, but allies at present. Infect a simulated colon tumor microenvironment. MCP. Agent Cancer. 2018;13:9. doi:10.1186/s13027-018-0180-y. 2012;11:851–862. doi:10.1074/mcp.M112.019315. 18. Lukasiewicz K, Fol M. Microorganisms in the treatment 30. Tjalsma H, Bolhuis A, Jongbloed JD, Bron S, van of cancer: advantages and limitations. J Immunol Res. Dijl JM. Signal peptide-dependent protein transport in 2018;2018:2397808. doi:10.1155/2018/2397808. Bacillus subtilis: a genome-based survey of the 19. Forbes NS, Coffin RS, Deng L, Evgin L, Fiering S, secretome. MMBR. 2000;64:515–547. Giacalone M, Gravekamp C, Gulley JL, Gunn H, 31. Rubinstein MR, Wang X, Liu W, Hao Y, Cai G, Han YW. Hoffman RM, et al. White paper on microbial Fusobacterium nucleatum promotes colorectal carcino­ anti-cancer therapy and prevention. J ImmunoTher genesis by modulating E-cadherin/beta-catenin signaling Cancer. 2018;6:78. doi:10.1186/s40425-018-0381-3. via its FadA adhesin. Cell Host Microbe. 2013;14:195–206. 20. Kramer MG, Masner M, Ferreira FA, Hoffman RM. doi:10.1016/j.chom.2013.07.012. Bacterial therapy of cancer: promises, limitations, and 32. Fardini Y, Wang X, Temoin S, Nithianantham S, Lee D, insights for future directions. Front Microbiol. Shoham M, Han YW. Fusobacterium nucleatum adhesin 2018;9:16. doi:10.3389/fmicb.2018.00016. FadA binds vascular endothelial cadherin and alters 21. Shen XJ, Rawls JF, Randall T, Burcal L, Mpande CN, endothelial integrity. Mol Microbiol. 2011;82:1468–1480. Jenkins N, Jovov B, Abdo Z, Sandler RS, Keku TO. doi:10.1111/j.1365-2958.2011.07905.x. Molecular characterization of mucosal adherent bac­ 33. Chen Y, Peng Y, Yu J, Chen T, Wu Y, Shi L, Li Q, Wu J, teria and associations with colorectal adenomas. Gut Fu X. Invasive Fusobacterium nucleatum activates Microbes. 2010;1:138–147. doi:10.4161/gmic.1.3.12360. beta-catenin signaling in colorectal cancer via a TLR4/ 22. Chen W, Liu F, Ling Z, Tong X, Xiang C. Human P-PAK1 cascade. Oncotarget. 2017;8:31802–31814. intestinal lumen and mucosa-associated microbiota in doi:10.18632/oncotarget.15992. patients with colorectal cancer. PloS One. 2012;7: 34. Donnenberg MS, Tacket CO, James SP, Losonsky G, e39743. doi:10.1371/journal.pone.0039743. Nataro JP, Wasserman SS, Kaper JB, Levine MM. Role 23. Flemer B, Lynch DB, Brown JM, Jeffery IB, Ryan FJ, of the eaeA gene in experimental enteropathogenic Claesson MJ, O'Riordain M, Shanahan F, O'Toole PW. Escherichia coli infection. J Clin Invest. Tumour-associated and non-tumour-associated micro­ 1993;92:1412–1417. doi:10.1172/JCI116717. biota in colorectal cancer. Gut. 2017;66:633–643. 35. Jerse AE, Yu J, Tall BD, Kaper JB. A genetic locus of doi:10.1136/gutjnl-2015-309595. enteropathogenic Escherichia coli necessary for the pro­ 24. Zeller G, Tap J, Voigt AY, Sunagawa S, Kultima JR, duction of attaching and effacing lesions on tissue cul­ Costea PI, Amiot A, Bohm J, Brunetti F, Habermann ture cells. Proc Natl Acad Sci U S A. 1990;87:7839–7843. N, et al. Potential of fecal microbiota for early-stage doi:10.1073/pnas.87.20.7839. detection of colorectal cancer. Mol Syst Biol. 36. Maddocks OD, Short AJ, Donnenberg MS, Bader S, 2014;10:766. doi:10.15252/msb.20145645. Harrison DJ. Attaching and effacing Escherichia coli 25. Wang T, Cai G, Qiu Y, Fei N, Zhang M, Pang X, Jia W, Cai downregulate DNA mismatch repair protein in vitro S, Zhao L. Structural segregation of gut microbiota between and are associated with colorectal adenocarcinomas in e1799733-18 R. TADDESE ET AL.

humans. PloS One. 2009;4:e5517. doi:10.1371/journal. 48. Fukugaiti MH, Ignacio A, Fernandes MR, Ribeiro Junior U, pone.0005517. Nakano V, Avila-Campos MJ. High occurrence of 37. Rhee KJ, Wu S, Wu X, Huso DL, Karim B, Franco AA, Fusobacterium nucleatum and Clostridium difficile in the Rabizadeh S, Golub JE, Mathews LE, Shin J, et al. Induction intestinal microbiota of colorectal carcinoma patients. Braz of persistent colitis by a human commensal, enterotoxigenic J Microbiol [Publ Braz Soc Microbiol]. 2015;46:1135–1140. Bacteroides fragilis, in wild-type C57BL/6 mice. Infect doi:10.1590/S1517-838246420140665. Immun. 2009;77:1708–1718. doi:10.1128/IAI.00814-08. 49. Yamazaki K, Tsunoda A, Sibusawa M, Tsunoda Y, 38. Wu S, Morin PJ, Maouyo D, Sears CL. Bacteroides Kusano M, Fukuchi K, Yamanaka M, Kushima M, fragilis enterotoxin induces c-Myc expression and cel­ Nomoto K, Morotomi M. The effect of an oral admin­ lular proliferation. Gastroenterology. 2003;124:392 istration of Lactobacillus casei strain shirota on –400. doi:10.1053/gast.2003.50047. azoxymethane-induced colonic aberrant crypt foci and 39. Cuevas-Ramos G, Petit CR, Marcq I, Boury M, colon cancer in the rat. Oncol Rep. 2000;7:977–982. Oswald E, Nougayrede JP. Escherichia coli induces doi:10.3892/or.7.5.977. DNA damage in vivo and triggers genomic instability 50. Kato-Kataoka A, Nishida K, Takada M, Kawai M, in mammalian cells. Proc Natl Acad Sci U S A. Kikuchi-Hayakawa H, Suda K, Ishikawa H, Gondo Y, 2010;107:11537–11542. doi:10.1073/pnas.1001261107. Shimizu K, Matsuki T, et al. Fermented milk containing 40. Arthur JC, Perez-Chanona E, Muhlbauer M, lactobacillus casei strain shirota preserves the diversity Tomkovich S, Uronis JM, Fan TJ, Campbell BJ, of the gut microbiota and relieves abdominal dysfunc­ Abujamel T, Dogan B, Rogers AB, et al. Intestinal tion in healthy medical students exposed to academic inflammation targets cancer-inducing activity of the stress. Appl Environ Microbiol. 2016;82:3649–3658. microbiota. Science (New York, NY). 2012;3 doi:10.1128/AEM.04134-15. 38:120–123. doi:10.1126/science.1224820. 51. Morishita T, Fukada T, Shirota M, Yura T. Genetic basis 41. Wilson MR, Jiang Y, Villalta PW, Stornetta A, Boudreau of nutritional requirements in Lactobacillus casei. PD, Carra A, Brennan CA, Chun E, Ngo L, Samson LD, J Bacteriol. 1974;120:1078–1084. doi:10.1128/JB.120 et al. The human gut bacterial genotoxin colibactin .3.1078-1084.1974. alkylates DNA. Science (New York, NY). 2019;363. 52. Derrien M, Vaughan EE, Plugge CM, de Vos WM. 42. Wattam AR, Davis JJ, Assaf R, Boisvert S, Brettin T, Bun C, Akkermansia muciniphila gen. nov., sp. nov., Conrad N, Dietrich EM, Disz T, Gabbard JL, et al. a human intestinal mucin-degrading bacterium. Improvements to PATRIC, the all-bacterial bioinformatics Int J Syst Evol Microbiol. 2004;54:1469–1476. doi:10.1 database and analysis resource center. Nucleic Acids Res. 099/ijs.0.02873-0. 2017;45:D535–d42. doi:10.1093/nar/gkw1017. 53. Dejea CM, Fathi P, Craig JM, Boleij A, Taddese R, Geis 43. Boleij A, van Gelder MM, Swinkels DW, Tjalsma H. AL, Wu X, DeStefano Shields CE, Hechenbleikner EM, Clinical Importance of Streptococcus gallolyticus infec­ Huso DL, et al. Patients with familial adenomatous tion among colorectal cancer patients: systematic review polyposis harbor colonic biofilms containing tumori­ and meta-analysis. Clin Infect Dis Offl Publ Infect Dis genic bacteria. Science (New York, NY). Soc Am. 2011;53:870–878. doi:10.1093/cid/cir609. 2018;359:592–597. doi:10.1126/science.aah3648. 44. Wentling GK, Metzger PP, Dozois EJ, Chua HK, 54. Weir TL, Manter DK, Sheflin AM, Barnett BA, Krishna M. Unusual bacterial infections and colorectal Heuberger AL, Ryan EP. Stool microbiome and meta­ carcinoma–Streptococcus bovis and Clostridium septi­ bolome differences between colorectal cancer patients cum: report of three cases. Dis Colon Rectum. and healthy adults. PloS One. 2013;8:e70803. 2006;49:1223–1227. doi:10.1007/s10350-006-0576-4. doi:10.1371/journal.pone.0070803. 45. Schaaf RE, Jacobs N, Kelvin FM, Gallis HA, Akwari O, 55. Dingemanse C, Belzer C, van Hijum SA, Gunthel M, Thompson WM. Clostridium septicum infection asso­ Salvatori D, den Dunnen JT, Kuijper EJ, Devilee P, de ciated with colonic carcinoma and hematologic Vos WM, van Ommen GB, et al. Akkermansia mucini­ abnormality. Radiology. 1980;137:625–627. doi:10.1148 phila and Helicobacter typhlonius modulate intestinal /radiology.137.3.6934562. tumor development in mice. Carcinogenesis. 46. Sidhu JS, Mandal A, Virk J, Gayam V. Early detection of 2015;36:1388–1396. doi:10.1093/carcin/bgv120. colon cancer following incidental finding of 56. Knapp O, Maier E, Mkaddem SB, Benz R, Bens M, Clostridium septicum bacteremia. J Invest Med High Chenal A, Geny B, Vandewalle A, Popoff MR. Impact Case Rep. 2019;7:2324709619832050. doi:10. Clostridium septicum alpha-toxin forms pores and 1177/2324709619832050. induces rapid cell necrosis. Toxicon. 2010;55:61–72. 47. Zheng Y, Luo Y, Lv Y, Huang C, Sheng Q, Zhao P, Ye J, doi:10.1016/j.toxicon.2009.06.037. Jiang W, Liu L, Song X, et al. Clostridium difficile 57. Wust J, Hardegger U. Transferable resistance to clinda­ colonization in preoperative colorectal cancer patients. mycin, erythromycin, and tetracycline in Clostridium Oncotarget. 2017;8:11877–11886. doi:10.18632/onco difficile. Antimicrob Agents Chemother. 1983;23: target.14424. 784–786. doi:10.1128/AAC.23.5.784. GUT MICROBES e1799733-19

58. Boleij A, Muytjens CM, Bukhari SI, Cayet N, Glaser P, 70. Poisson Distribution. Univariate Discrete Distributions. Hermans PW, Swinkels DW, Bolhuis A, Tjalsma H. 2005;156–207. Novel clues on the specific association of 71. Graham FL, Smiley J, Russell WC, Nairn R. Streptococcus gallolyticus subsp gallolyticus with color­ Characteristics of a human cell line transformed by ectal cancer. J Infect Dis. 2011;203:1101–1109. DNA from human adenovirus type 5. J Gen Virol. doi:10.1093/infdis/jiq169. 1977;36:59–74. doi:10.1099/0022-1317-36-1-59. 59. Tripodi MF, Fortunato R, Utili R, Triassi M, Zarrilli R. 72. Ma CT, Luo HS, Gao F, Tang QC, Chen W. Molecular epidemiology of Streptococcus bovis causing Fusobacterium nucleatum promotes the progression of endocarditis and bacteraemia in Italian patients. Clin colorectal cancer by interacting with E-cadherin. Oncol Microbiol Infect Off Publ Eur Soc Clin Microbiol Infect Lett. 2018;16:2606–2612. doi:10.3892/ol.2018.8947. Dis. 2005;11:814–819. doi:10.1111/j.1469-0691.2005 73. Dalmasso G, Cougnoux A, Delmas J, Darfeuille- .01248.x. Michaud A, Bonnet R. The bacterial genotoxin colibac­ 60. Tripodi MF, Adinolfi LE, Ragone E, Durante Mangoni tin promotes colon tumor growth by modifying the E, Fortunato R, Iarussi D, Ruggiero G, Utili R. tumor microenvironment. Gut Microbes. Streptococcus bovis endocarditis and its association 2014;5:675–680. doi:10.4161/19490976.2014.969989. with chronic liver disease: an underestimated risk 74. Fais T, Delmas J, Barnich N, Bonnet R, Dalmasso G. factor. Clin Infect Dis Offl Publ Infect Dis Soc Am. Colibactin: more than a new bacterial toxin. Toxins. 2004;38:1394–1400. doi:10.1086/392503. 2018;10. doi:10.3390/toxins10040151. 61. Ogawa Y, Ooka T, Shi F, Ogura Y, Nakayama K, 75. Dean P, Kenny B. The effector repertoire of enteropathogenic Hayashi T, Shimoji Y. The genome of Erysipelothrix E. coli: ganging up on the host cell. Curr Opin Microbiol. rhusiopathiae, the causative agent of swine erysipelas, 2009;12:101–109. doi:10.1016/j.mib.2008.11.006. reveals new insights into the evolution of firmicutesand 76. Singh AP, Sharma S, Pagarware K, Siraji RA, Ansari I, the organism’s intracellular adaptations. J Bacteriol. Mandal A, Walling P, Aijaz S. Enteropathogenic E. coli 2011;193:2959–2971. doi:10.1128/JB.01500-10. effectors EspF and Map independently disrupt tight 62. Taddese R, Belzer C, Aalvink S, de Jonge MI, Nagtegaal junctions through distinct mechanisms involving tran­ ID, Dutilh BE, Boleij A. Bacterial zombies and ghosts: scriptional and post-transcriptional regulation. Sci Rep. production of inactivated gram-positive and 2018;8:3719. doi:10.1038/s41598-018-22017-1. gram-negative species with preserved cellular morphol­ 77. Wassenaar TM. E. coli and colorectal cancer: a complex ogy and cytoplasmic content. bioRxiv. 2018;458158. relationship that deserves a critical mindset. Crit Rev 63. Ahmed D, Eide PW, Eilertsen IA, Danielsen SA, Eknaes Microbiol. 2018;44:619–632. doi:10.1080/1040841 M, Hektoen M, Lind GE, Lothe RA. Epigenetic and X.2018.1481013. genetic features of 24 colon cancer cell lines. 78. Bossuet-Greif N, Vignard J, Taieb F, Mirey G, Dubois Oncogenesis. 2013;2:e71. doi:10.1038/oncsis.2013.35. D, Petit C, Oswald E, Nougayrede JP. The colibactin 64. Eijkelenboom A, Kamping EJ, Kastner-van Raaij AW, genotoxin generates DNA Interstrand cross-links in Hendriks-Cornelissen SJ, Neveling K, Kuiper RP, infected cells. mBio. 2018;9. Hoischen A, Nelen MR, Ligtenberg MJ, Tops BB. Reliable 79. Ahn J, Sinha R, Pei Z, Dominianni C, Wu J, Shi J, next-generation sequencing of formalin-fixed, Goedert JJ, Hayes RB, Yang L. Human gut microbiome paraffin-embedded tissue using single molecule tags. JMD. and risk for colorectal cancer. J Natl Cancer Inst. 2016;18:851–863. doi:10.1016/j.jmoldx.2016.06.010. 2013;105:1907–1911. doi:10.1093/jnci/djt300. 65. Mosmann T. Rapid colorimetric assay for cellular 80. Yang Y, Weng W, Peng J, Hong L, Yang L, Toiyama Y, Gao growth and survival: application to proliferation and R, Liu M, Yin M, Pan C, et al. Fusobacterium nucleatum cytotoxicity assays. J Immunol Methods. increases proliferation of colorectal cancer cells and tumor 1983;65:55–63. doi:10.1016/0022-1759(83)90303-4. development in mice by activating toll-like receptor 4 signal­ 66. van der Maaten LH, Geoffrey. Visualizing data using ing to nuclear factor-kappaB, and up-regulating expression of t-SNE. J Mach Learn Res. 2008;9:2579–2605. MicroRNA-21. Gastroenterology. 2017;152:851–66.e24. 67. Bentley JL. Multidimensional binary search trees used doi:10.1053/j.gastro.2016.11.018. for associative searching. Commun ACM. 1975; 81. Castellarin M, Warren RL, Freeman JD, Dreolini L, 18:509–517. Krzywinski M, Strauss J, Barnes R, Watson P, Allen- 68. Ballard J, Sokolov Y, WL Y, BL K, Tweten RK. Vercoe E, Moore RA, et al. Fusobacterium nucleatum infec­ Activation and mechanism of Clostridium septicum tion is prevalent in human colorectal carcinoma. Genome alpha toxin. Mol Microbiol. 1993;10:627–634. Res. 2012;22:299–306. doi:10.1101/gr.126516.111. 69. Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, 82. Liu J, Hsieh CL, Gelincik O, Devolder B, Sei S, Zhang S, Edwards RA, Formsma K, Gerdes S, Glass EM, Kubal Lipkin SM, Chang YF. Proteomic characterization of M, et al. The RAST Server: rapid annotations using outer membrane vesicles from gut mucosa-derived subsystems technology. BMC Genomics. 2008;9:75. fusobacterium nucleatum. J Proteomics. doi:10.1186/1471-2164-9-75. 2019;195:125–137. doi:10.1016/j.jprot.2018.12.029. e1799733-20 R. TADDESE ET AL.

83. Han YW, Ikegami A, Rajanna C, Kawsar HI, Zhou Y, Li M, 91. Kiersztyn B, Siuda W, Chrost RJ. Persistence of bacterial Sojar HT, Genco RJ, Kuramitsu HK, Deng CX. Identification proteolytic enzymes in lake ecosystems. FEMS and characterization of a novel adhesin unique to oral Microbiol Ecol. 2012;80:124–134. doi:10.1111/j.1574- fusobacteria. J Bacteriol. 2005;187:5330–5340. doi:10.1128/ 6941.2011.01276.x. JB.187.15.5330-5340.2005. 92. Battaglia-Hsu SF, Akchiche N, Noel N, Alberto JM, 84. Sears CL. The toxins of Bacteroides fragilis. Toxicon. Jeannesson E, Orozco-Barrios CE, Martinez-Fong D, 2001;39:1737–1746. doi:10.1016/S0041-0101(01)00160-X. Daval JL, Gueant JL. Vitamin B12 deficiency reduces 85. Jans C, Boleij A. The road to infection: host-microbe proliferation and promotes differentiationof neuroblas­ interactions definingthe pathogenicity of Streptococcus toma cells and up-regulates PP2A, proNGF, and TACE. bovis/Streptococcus equinus complex members. Front Proc Natl Acad Sci U S A. 2009;106:21930–21935. Microbiol. 2018;9:603. doi:10.3389/fmicb.2018.00603. doi:10.1073/pnas.0811794106. 86. Boleij A, Tjalsma H. The itinerary of Streptococcus 93. Wexler AG, Schofield WB, Degnan PH, Folta-Stogniew gallolyticus infection in patients with colonic malignant E, Barry NA, Goodman AL. Human gut Bacteroides disease. Lancet Infect Dis. 2013;13:719–724. doi:10.10 capture vitamin B12 via cell surface-exposed 16/S1473-3099(13)70107-5. lipoproteins. Elife. 2018;7. doi:0.7554/eLife.37138. 87. Kumar R, Herold JL, Schady D, Davis J, Kopetz S, Martinez- 94. Patel D, Witt SN. Ethanolamine and Moczygemba M, Murray BE, Han F, Li Y, Callaway E, et al. Phosphatidylethanolamine: partners in Health and Streptococcus gallolyticus subsp. gallolyticus promotes col­ Disease. Oxid Med Cell Longev. 2017;2017:4829180. orectal tumor development. PLoS Pathog. 2017;13: doi:10.1155/2017/4829180. e1006440. doi:10.1371/journal.ppat.1006440. 95. Tsoy O, Ravcheev D, Mushegian A. Comparative geno­ 88. Yang J, Zhang W, Evans PM, Chen X, He X, Liu C. mics of ethanolamine utilization. J Bacteriol. Adenomatous polyposis coli (APC) differentially regu­ 2009;191:7157–7164. doi:10.1128/JB.00838-09. lates beta-catenin phosphorylation and ubiquitination 96. Kaval KG, Garsin DA. Ethanolamine utilization in in colon cancer cells. J Biol Chem. 2006;281: bacteria. mBio. 2018;9. doi:0.1128/mBio.00066-18. 17751–17757. doi:10.1074/jbc.M600831200. 97. Kendall MM, Gruber CC, Parker CT, Sperandio V. 89. Tate JG, Bamford S, Jubb HC, Sondka Z, Beare DM, Bindal Ethanolamine controls expression of genes encoding compo­ N, Boutselakis H, Cole CG, Creatore C, Dawson E, et al. nents involved in interkingdom signaling and virulence in COSMIC: the Catalogue Of Somatic Mutations In Cancer. enterohemorrhagic Escherichia coli O157:H7. mBio. 2012;3. Nucleic Acids Res. 2019;47:D941–d7. doi:10.1093/nar/ doi:10.1128/mBio.00050-12. gky1015. 98. van de Wetering M, Francies HE, Francis JM, 90. Sgro GG, Oka GU, Souza DP, Cenens W, Bayer-Santos Bounova G, Iorio F, Pronk A, van Houdt W, van E, Matsuyama BY, Bueno NF, Dos Santos TR, Alvarez- Gorp J, Taylor-Weiner A, Kester L, et al. Prospective Martinez CE, Salinas RK, et al. Bacteria-killing Type IV derivation of a living organoid biobank of colorectal secretion systems. Front Microbiol. 2019;10:1078. cancer patients. Cell. 2015;161:933–945. doi:10.1016/ doi:10.3389/fmicb.2019.01078. j.cell.2015.03.053.